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  • 1 provides a theoretical and empirical analysis of the use of Centralized Critics in CTDE.
  • 2 introduces a new mutual information framework for MARL. This leads to the development of an algorithm called Variational Maximum Mutual Information, Multi-Agent Actor Critic which allows agents to coordinate simultaneous actions without latency.

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  1. Lyu et al. (2023) On Centralized Critics in Multi-Agent Reinforcement Learning

  2. Kim, Jung, Cho, Sung (2020) A Maximum Mutual Information Framework for Multi-Agent Reinforcement Learning